When comparing Splunk vs jKool, the Slant community recommends Splunk for most people. In the question“What are the best log management, aggregation & monitoring tools?”Splunk is ranked 11th while jKool is ranked 35th. The most important reason people chose Splunk is:

It's human readable, intuitive, fast and with auto-complete to boot. And if you need more advanced functionality out of your queries, [120+ page search manual](http://docs.splunk.com/index.php?title=Documentation:Splunk:Search:Whatsinthismanual:6.0beta&action=pdfbook) will give you an insight in how much is actually possible.

Pros

Pro

Easy to use, powerful search

It's human readable, intuitive, fast and with auto-complete to boot. And if you need more advanced functionality out of your queries, 120+ page search manual will give you an insight in how much is actually possible.

Pro

Widely used

De facto standard for log aggregation, monitoring, analysis and reporting.

Pro

Scales effortlessly

It is built for enterprise use, meaning it scales easily.

Pro

Real-time graphs

You can create visualizations that update in real time.

Pro

Cross-platform

OS X, Linux & Windows are supported. You can also access Splunk from iOS and Android devices.

Pro

Free version

With restrictions on log size and devices a free version is available.

Pro

Alerts

Splunk can turn searches into alerts.

Pro

Understands data in any format or language

Pro

Extendable via a large selection of apps

Pro

Subscriptions to real-time updates

Subscriptions to real-time updates from infrastructure systems gives users proactive detection of application anomalies, as well as performance, availability and capacity issues. This enables users to capture perishable insights into application issues that they would normally miss.

Pro

Offers free option

JKool offers free option limited by daily data volume and retention. Easy to sign up and try. No commitment or credit card required to signup.

Pro

Open source connectors

Pro

Analyze logs: syslog, log4j, logback and others

You can use the jKool log collectors to stream syslogs and other logs to a jKool and be able to view and analyze your logs in a graphical oriented way. jKool can show error rates, anomalies, exceptions, groups, time buckets, time windows, aggregations and apply math functions across all your logs.

Pro

Supports Logstash as a datasource

jKool can consume incoming streams directly from Logstash. Combine Logstash with other streams to deliver a unified application view. Logstash integration is open source.

Pro

Automatic anomaly detection

Pro

Unique Visualization

Visualization is generated dynamically based on a data query as opposed to the typical canned views that have nothing to do with the specific query.

Pro

More than log analyzer

jKool does much more than just log analysis. Examples: end-user monitoring, application performance, transaction tracking, business metrics and IoT. Developers can use APIs (java, REST) to build extensions for streaming, visualization. jKool provides a unified model for all time series machine data.

Pro

Simple, easy to use, great UI

There are really only 2 things a user needs to do to show charts, graphs: 1) create a dashboard 2) Create viewlets. Each viewlets is bound with a JQKL query. JQKL queries can be typed in or built via a query builder for beginners. Pretty easy to get up and running without learning JQKL. There is also a UI tutorial once you logon to jKool.

Pro

Self service dashboard for users with different responsibilities.

Provides situational awareness to users from their own perspective. The benefits are translated to reduction of support calls and visibility for each user, from their own angles into root causes of problems within a couple of clicks.

Pro

Unified analytics support

Combines analytics for events, metrics (name, value pairs) and transactions with real-time and historical analytics in a single platform.

Pro

Transaction Tracking & Discovery

jKool is able to automatically connect/stitch multiple events coming from multiple sources into a business transaction(s), measure performance, completion, progress. Transactions can be grouped into user defined sets (payment, claims, etc).

Pro

Simple model: Stream Data->Run Queries->Analyze

Easy to use cloud based log and application analytics supporting standards such as Syslog, log4j, log files, end-user monitoring, transaction tracking. No schemas to define, agentless, no servers or storage to setup. Provides true transaction stitching and analytics -- track all transactions, 100% of the time. On-premise and cloud based (docker support available).

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Cons

Con

Expensive

Splunk is pretty expensive compared to other solutions.

Con

Antiquated

The interface and service are very antiquated

Con

Seriously SLOW ingest

Their docs and sales say it will ingest up to 20k EPS, but reality is more like 1k eps per server.

Con

Complex set up process

Con

Doesn't seem to be very popular

JKool is a relatively new tool, as such, there don't seem to be many third party guides and tutorials other than from official sources from the JKool team.

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